Overview of Record Linking Recommendations
Spark AI Record Linking Recommendations leverages generative AI to automatically identify and link data across key GRC elements within your Risk Cloud environment. It streamlines historically complex and labor-intensive control cross-mappings and empowers holistic GRC management by identifying relationships and linking Risks, Controls, Policies, and Incidents.
Two main use cases of Spark AI Record Linking Recommendations are:
- Control Cross-Mapping: If you're working on an internal control record and need to find related controls across different frameworks (such as SCF, NIST, SOC2), Spark AI Record Linking Recommendations will suggest relevant controls with a click.
- Holistic GRC data elements linking: You can generate recommendations across various GRC data elements. The more modules you have enabled in your Risk Cloud environment, the more diverse and extensive the recommendations will be. For example, from a Risk record, Spark AI Record Linking Recommendations will suggest Controls that mitigate the risk and by linking them you can monitor your risk posture real-time. You can also get recommendations to link Regulation Requirements with Policies that serve as evidence for a control and gain confidence in regulation compliance.
How to Enable Record Linking Recommendations (RLR) for your Environment
System Administrators can enable Spark AI and its features by navigating to the Risk Cloud Spark AI Card on the Integrations page. This includes a toggle to activate the Record Linking Recommendations (RLR) feature
- Note: Once Spark AI RLR is enabled at the environment level, RLR will be disabled by default for all records and steps. To use RLR, you must manually enable it within the Linked Workflow section of each individual workflow (see Configuring Builder Settings for RLR for instructions).
Configuring Builder Settings for RLR
1. By default, RLR is disabled for all your Linked Workflow Sections. It must be configured before it is enabled.
2. To enable RLR, navigate to the Step where your Linked Workflow Setting resides and click Configure.
3. You must select at least 1 field used in each workflow. We recommend choosing the most relevant fields, such as your primary field and any descriptive fields that provide context for the records. Spark AI will parse the field values on records for the fields you select in this configuration.
4. Once this is configured, you'll now see that Spark AI Recommendations are enabled. You can always disable or edit configurations.
Using the Record Linking Recommendations on Records
Once you (the admin user) enabled and configured Spark AI Record Linking Recommendations, standard users can follow these steps to get started using RLR.
1. Navigate to the record where you want to generate linked record recommendations and have linked workflow set up in the step configurations. You will see the Recommendations tab as an option within the linked record section. Click on this tab to access the recommendations feature.
2. On the Recommendations tab, click the Generate Recommendations button. Spark AI will automatically provide top suggestions based on your current record within seconds.
3. After reviewing the automated recommendations, you can link any records by licking Link button. Then you will see this record in the "View linked records" tab. You can always refresh the record page to re-generate top recommendations at any time.